Sambaiga

Welcome to my website!

I am a Lead Data Scientist at the Centre for Intelligent Power (CIP) at Eaton in Dublin, Ireland. In my role, I lead the development of data analytics and machine learning powered products and services that contribute to intelligent power systems.

Before joining CIP Eaton, I served as a Senior Industrial Analytics Researcher in Irish Manufacturing (IMR), Dublin, Ireland. There, I developed and executed data analytics and AI-based solutions to empower manufacturers located in Ireland to embrace and lead the Industrial 4.0 revolution as early adopters and frontrunners. Prior to that, I worked as a Data Scientist and ML Researcher at CeADAR, a research center affiliated with University College Dublin, Ireland. I also served as a Machine Learning Researcher at IDLab, Imec at the University of Ghent, Belgium.

In addition to my extensive industry experience, I am currently finalizing my PhD in Computer Science and Engineering at ITI/LARSyS, Técnico Lisboa in Portugal under Prof Nuno Jardim Nunes and Dr. Lucas Pereira supervision.

I hold a Master’s degree in Leadership, Innovation and Technology from Technological University Dublin in partnership with Technology Ireland ICT. I also hold a second MSc degree in Telecommunication Engineering from the University of Dodoma, Tanzania.

Interest

I specialize in applied machine learning and strategic innovation management, focusing on leveraging these fields to address real-world business challenges and drive competitive advantage. In the realm of applied machine learning, my research interests include forecasting, non-intrusive load monitoring, and time-series analysis for applications such as predictive maintenance and power grid management. From a strategic management perspective, I am interested in business model innovation, strategic roadmaps, and innovation management.

Sharing and Learning:

I am also passionate about sharing knowledge and fostering collaboration. I maintain a repository on GitHub with resources on learning and applying AI for practical problems.

Please feel free to explore my website to learn more about my work, research interests, and academic background. I’m always interested in connecting with others who share my passion for data science, AI, and innovation.

selected publications

  1. MLPQF
    Efficiency through Simplicity: MLP-based Approach for Net-Load Forecasting with Uncertainty Estimates in Low-Voltage Distribution Networks
    Faustine, Anthony, Nunes, Nuno Jardim, and Pereira, Lucas
    IEEE Transactions on Power Systems 2024
  2. DeepNLMTK
    Unlocking the Full Potential of Neural NILM: On Automation, Hyperparameters and Modular Pipelines
    IEEE Transactions on Industrial Informatics 2022
  3. FPSeq2Q
    FPSeq2Q: Fully Parameterized Sequence to Quantile Regression for Net-Load Forecasting with Uncertainty Estimates
    Faustine, Anthony, and Pereira, Lucas
    IEEE Transactions on Smart Grid 2022
  4. AWRGNILM
    Adaptive Weighted Recurrence Graphs for Appliance Recognition in Non-Intrusive Load Monitoring
    Faustine, Anthony, Pereira, Lucas, and Klemenjak, Christoph
    IEEE Transactions on Smart Grid 2021